Discover everything you need to know about foot traffic – what it is, how to measure it, and how foot traffic can be leveraged to help your business.
Foot traffic refers to the movement of pedestrians from place to place. In business, foot traffic (sometimes called “footfall”) is a metric used to measure the number of people who visit a particular venue or location during a specified period of time. Foot traffic data also provides visibility into the behavior and characteristics of visitors to various locations.
Professionals across industries analyze foot traffic patterns to understand human behavior and movement in the physical world:
In the past, practitioners had to rely on outdated methods like manual counting, motion sensors, focus groups, and customer interviews to understand foot traffic patterns and the habits and preferences of visitors to different places. But today, developments in AI and machine learning make it possible for businesses and other stakeholders to easily and efficiently glean actionable insights from foot traffic. With the help of aggregated and de-identified location data from mobile devices, location intelligence platforms provide highly accurate and customizable foot traffic analytics. These analytics reveal not just how many people visit a specific place, but also where they come from and where else they go – without compromising individual privacy.
Mobile-powered foot traffic analytics are also incredibly versatile. Practitioners can define for themselves the geographical scopes of the locations to be analyzed, as well as the relevant time periods. They can then analyze their customized audiences with other geospatial datasets, to determine the habits, characteristics, profiles, and preferences of people that visit particular places at particular times. The possibilities are virtually endless:
Zooming in and out: Foot traffic can be tracked and analyzed on almost any geographical level – whether nationwide, statewide, city-wide, or for specific locations. Geographic locations – including cities, retail corridors, business districts, and even specific buildings – can be defined as points of interest (POIs) where visitation patterns can be observed. Data can be aggregated, to allow for chain-level, market-level or other macro analyses, or broken down into hyper-local, bite-size pieces.
Competitive Benchmarking: Location analytics offer practitioners visibility into what’s happening not only in their own venues, but also at those of the competition. By analyzing foot traffic to other chains, locations, shopping centers, and geographical areas, professionals can conduct both broad and highly specific comparative benchmarking.
Analyzing changes over time: Changes and trends in foot traffic patterns can be analyzed on daily, hourly, monthly, or yearly bases, allowing professionals to measure the actual impacts of different strategies and determine performance over time.
Understanding visitor profiles: By combining foot traffic data with demographic, psychographic, and other datasets – and really, the sky’s the limit – analysts can conduct deep analyses of the defined audiences.
The importance of foot traffic for business and civic stakeholders, and the specific kinds of insights that can be derived from its analysis, can be explained with a few concrete examples:
Imagine you run a small chain of local grocery stores. By tracking foot traffic to each of your locations, you can:
Now imagine you’re a local government employee working with a Destination Marketing Organization (DMO) to make your city a more attractive tourist destination. Analyzing foot traffic patterns allows you to:
Suppose you represent a CPG company that is launching a new high-protein, vegan yogurt and wants to ensure that the product is placed with the right retailers. By leveraging foot traffic data you can:
These are just a few of the ways that foot traffic patterns can be harnessed to generate business intelligence that drives informed decision-making. For additional examples and use cases across industries, check out more of our Guides here.
Given the high stakes of decisions based on foot traffic data, it is critical to choose a location intelligence platform that is accurate, precise, comprehensive, and user-friendly – and that is truly committed to protecting privacy.
Placer.ai’s location intelligence solution checks all these crucial boxes – providing professionals across industries with the tools they need to instantly analyze foot traffic for any specific commercial location or broader geographical area. Placer harnesses advanced data science and machine learning techniques to extrapolate foot traffic analytics from representative panels of de-identified location data. And with Placer’s user-friendly platform, anyone can quickly and efficiently analyze visitation to chains, stores, and other points of interest (POIs) nationwide.
Placer also features a broad range of psychographic and demographic datasets that customers can easily integrate into their analyses – as well as tools that can instantly process all the relevant information to find ideal locations for retailers and perfect tenants for shopping centers. To ensure privacy, all of Placer’s data is stripped of identifiers before it reaches the company – and provided to customers only in the form of aggregated, statistical information about physical locations.
Foot traffic – the foundation of any good location analytics platform – is a critical metric for understanding how people behave and where they go in the real world. By analyzing foot traffic, retailers, urban planners, CRE brokers, and others can gain valuable insights into consumer behavior, make informed decisions, and improve outcomes. As location intelligence capabilities continue to develop and become ever more sophisticated, access to accurate and up-to-date foot traffic data will become a must-have for businesses across industries.